Toward Modular Soft Robotics: Proprioceptive Curvature Sensing and Sliding-Mode Control of Soft Bidirectional Bending Modules
Real-world environments are complex, unstructured, and often fragile. Soft robotics offers a solution for robots to safely interact with the environment and human coworkers, but suffers from a host of challenges in sensing and control of continuously deformable bodies. To overcome these challenges,...
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Published in | Soft robotics Vol. 4; no. 2; p. 117 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
01.06.2017
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Subjects | |
Online Access | Get more information |
ISSN | 2169-5180 |
DOI | 10.1089/soro.2016.0041 |
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Abstract | Real-world environments are complex, unstructured, and often fragile. Soft robotics offers a solution for robots to safely interact with the environment and human coworkers, but suffers from a host of challenges in sensing and control of continuously deformable bodies. To overcome these challenges, this article considers a modular soft robotic architecture that offers proprioceptive sensing of pressure-operated bending actuation modules. We present integrated custom magnetic curvature sensors embedded in the neutral axis of bidirectional bending actuators. We describe our recent advances in the design and fabrication of these modules to improve the reliability of proprioceptive curvature feedback over our prior work. In particular, we study the effect of dimensional parameters on improving the linearity of curvature measurements. In addition, we present a sliding-mode controller formulation that drives the binary solenoid valve states directly, giving the control system the ability to hold the actuator steady without continuous pressurization and depressurization. In comparison to other methods, this control approach does not rely on pulse width modulation and hence offers superior dynamic performance (i.e., faster response rates). Our experimental results indicate that the proposed soft robotic modules offer a large range of bending angles with monotonic and more linear embedded curvature measurements, and that the direct sliding-mode control system exhibits improved bandwidth and a notable reduction in binary valve actuation operations compared to our earlier iterative sliding-mode controller. |
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AbstractList | Real-world environments are complex, unstructured, and often fragile. Soft robotics offers a solution for robots to safely interact with the environment and human coworkers, but suffers from a host of challenges in sensing and control of continuously deformable bodies. To overcome these challenges, this article considers a modular soft robotic architecture that offers proprioceptive sensing of pressure-operated bending actuation modules. We present integrated custom magnetic curvature sensors embedded in the neutral axis of bidirectional bending actuators. We describe our recent advances in the design and fabrication of these modules to improve the reliability of proprioceptive curvature feedback over our prior work. In particular, we study the effect of dimensional parameters on improving the linearity of curvature measurements. In addition, we present a sliding-mode controller formulation that drives the binary solenoid valve states directly, giving the control system the ability to hold the actuator steady without continuous pressurization and depressurization. In comparison to other methods, this control approach does not rely on pulse width modulation and hence offers superior dynamic performance (i.e., faster response rates). Our experimental results indicate that the proposed soft robotic modules offer a large range of bending angles with monotonic and more linear embedded curvature measurements, and that the direct sliding-mode control system exhibits improved bandwidth and a notable reduction in binary valve actuation operations compared to our earlier iterative sliding-mode controller. |
Author | Skorina, Erik H Luo, Ming Tao, Weijia Sun, Yinan Ozel, Selim Chen, Fuchen Onal, Cagdas D |
Author_xml | – sequence: 1 givenname: Ming surname: Luo fullname: Luo, Ming organization: WPI Soft Robotics Lab, Mechanical Engineering Department, Robotics Engineering Program, Worcester Polytechnic Institute , Worcester, Massachusetts – sequence: 2 givenname: Erik H surname: Skorina fullname: Skorina, Erik H organization: WPI Soft Robotics Lab, Mechanical Engineering Department, Robotics Engineering Program, Worcester Polytechnic Institute , Worcester, Massachusetts – sequence: 3 givenname: Weijia surname: Tao fullname: Tao, Weijia organization: WPI Soft Robotics Lab, Mechanical Engineering Department, Robotics Engineering Program, Worcester Polytechnic Institute , Worcester, Massachusetts – sequence: 4 givenname: Fuchen surname: Chen fullname: Chen, Fuchen organization: WPI Soft Robotics Lab, Mechanical Engineering Department, Robotics Engineering Program, Worcester Polytechnic Institute , Worcester, Massachusetts – sequence: 5 givenname: Selim surname: Ozel fullname: Ozel, Selim organization: WPI Soft Robotics Lab, Mechanical Engineering Department, Robotics Engineering Program, Worcester Polytechnic Institute , Worcester, Massachusetts – sequence: 6 givenname: Yinan surname: Sun fullname: Sun, Yinan organization: WPI Soft Robotics Lab, Mechanical Engineering Department, Robotics Engineering Program, Worcester Polytechnic Institute , Worcester, Massachusetts – sequence: 7 givenname: Cagdas D surname: Onal fullname: Onal, Cagdas D organization: WPI Soft Robotics Lab, Mechanical Engineering Department, Robotics Engineering Program, Worcester Polytechnic Institute , Worcester, Massachusetts |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29182091$$D View this record in MEDLINE/PubMed |
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Title | Toward Modular Soft Robotics: Proprioceptive Curvature Sensing and Sliding-Mode Control of Soft Bidirectional Bending Modules |
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